Modulating the host immune response to tumors holds considerable potential for cancer treatment opportunities, yet directly assaying gene expression of immune cells in tumors remains challenging. The immune component of the tumor might represent a relatively small fraction of cells, and different cancers might have different somatic variants that could influence gene expression in complex ways. Computational methods to analyze the subset of immune cells present in a tumor must account for tumor-to-tumor variability, intratumoral heterogeneity, and the relatively low fraction of immune cells. To attack these obstacles, Li et al. developed a new computational approach to analyze immune cell infiltration in 23 cancer types.

The authors began with a straightforward assumption: Stroma-associated genes should be negatively correlated with tumor purity. That is, as the fraction of cancer cells increases, the relative abundance of genes expressed in stromal cells of the tumor microenvironment—including immune cells—should be reduced. This evaluation allowed them to select immune signature genes and infer relative abundance of immune cell types, providing a clearer picture of the host immune response to the tumor. This step was not included in existing approaches, and the authors’ results suggest that this filtering enables robust analysis across cancer types. In bladder cancer, glioblastoma, and lung adenocarcinoma, the authors observed an enrichment of B cell signatures in the tumor compared with adjacent normal tissue. These cases were also associated with longer survival time. To demonstrate that their data could be used to select potential cancer vaccine targets, the authors ranked genes by cancer specificity and correlation with CD8 T cell infiltration, which highlighted SPAG5 for its potential in multiple cancer types.

Computational deconvolution of the cell types present tumors and other solid tissues could reveal potential opportunities to identify lineage-specific markers or treatment opportunities. This large-scale evaluation of immunity across cancer types provides a snapshot of tumors when the biopsies were taken, but the dynamics of tumor growth, particularly under response to immunotherapies, are currently unaddressed. Although this is not the first method to address the challenge of immune cell type deconvolution in tumors, selecting stromal genes before deconvolution enables the authors to identify new associations and targets.